Challenges and future directions for energy, latency, and lifetime improvements in NVMs

Abstract

Recently, non-volatile memory (NVM) technology has revolutionized the landscape of memory systems. With many advantages, such as non volatility and near zero standby power consumption, these byte-addressable memory technologies are taking the place of DRAMs. Nonetheless, they also present some limitations, such as limited write endurance, which hinders their widespread use in today’s systems. Furthermore, adjusting current data management systems to embrace these new memory technologies and all their potential is proving to be a nontrivial task. Because of this, a substantial amount of research has been done, from both the database community and the storage systems community, that tries to improve various aspects of NVMs to integrate these technologies into the memory hierarchy. In this work, which is the extended version of Kargar and Nawab (Proc. VLDB Endowment 14(12):3194–3197, 2021), we explore state-of-the-art work on deploying NVMs in database and storage systems communities and the ways their limitations are being handled within these communities. In particular, we focus on (1) the challenges that are related to high energy consumption, low write endurance and asymmetric read/write costs and (2) how these challenges can be solved using hardware and software solutions, especially by reducing the number of bit flips in write operations. We believe that this area has not gained enough attention in the data management community and this tutorial will provide information on how to integrate recent advances from the NVM storage community into existing and future data management systems.

Innovation in Data Storage Technologies: From Cloud Computing to Edge Computing

“…The chapter also underscores the social and economic impact of big data storage technologies, highlighting open research challenges in this field. Kargar and Nawab (2023) explore the challenges associated with non-volatile memory (NVM) technologies, which are emerging as alternatives to traditional DRAMs. Despite their advantages like non-volatility and low standby power consumption, NVMs face limitations such as limited write endurance and high energy consumption, posing challenges for their integration into current data management systems.…”

“…They identify missing standards as a major technical barrier to the widespread adoption of big data storage technologies and call for addressing scalability issues in graph databases. Kargar and Nawab (2023) focus on the energy, latency, and lifetime improvements in NVMs. They discuss hardware and software solutions to reduce the number of bit flips in write operations, which is crucial for enhancing the performance and longevity of NVMs in data storage applications.…”